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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 new columns ({'seed'}) and 10 missing columns ({'pmid', 'entity_b_start', 'sentence_end', 'entity_b_end', 'entity_b_id', 'entity_a_start', 'entity_a_end', 'entity_a_id', 'label', 'sentence_start'}).
This happened while the csv dataset builder was generating data using
hf://datasets/DevWithKaiju/cell-cell-communication/pubmed/seed_splits.csv (at revision 206ebee01c426e829316cbcd6f35c88eeabccfe6), ['hf://datasets/DevWithKaiju/cell-cell-communication@206ebee01c426e829316cbcd6f35c88eeabccfe6/pubmed/relations.csv', 'hf://datasets/DevWithKaiju/cell-cell-communication@206ebee01c426e829316cbcd6f35c88eeabccfe6/pubmed/seed_splits.csv', 'hf://datasets/DevWithKaiju/cell-cell-communication@206ebee01c426e829316cbcd6f35c88eeabccfe6/semmed/relations.csv', 'hf://datasets/DevWithKaiju/cell-cell-communication@206ebee01c426e829316cbcd6f35c88eeabccfe6/semmed/seed_splits.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
seed: int64
id: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 485
to
{'id': Value('int64'), 'pmid': Value('int64'), 'label': Value('int64'), 'entity_a_id': Value('string'), 'entity_b_id': Value('string'), 'sentence_start': Value('int64'), 'sentence_end': Value('int64'), 'entity_a_start': Value('string'), 'entity_a_end': Value('string'), 'entity_b_start': Value('string'), 'entity_b_end': Value('string')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 new columns ({'seed'}) and 10 missing columns ({'pmid', 'entity_b_start', 'sentence_end', 'entity_b_end', 'entity_b_id', 'entity_a_start', 'entity_a_end', 'entity_a_id', 'label', 'sentence_start'}).
This happened while the csv dataset builder was generating data using
hf://datasets/DevWithKaiju/cell-cell-communication/pubmed/seed_splits.csv (at revision 206ebee01c426e829316cbcd6f35c88eeabccfe6), ['hf://datasets/DevWithKaiju/cell-cell-communication@206ebee01c426e829316cbcd6f35c88eeabccfe6/pubmed/relations.csv', 'hf://datasets/DevWithKaiju/cell-cell-communication@206ebee01c426e829316cbcd6f35c88eeabccfe6/pubmed/seed_splits.csv', 'hf://datasets/DevWithKaiju/cell-cell-communication@206ebee01c426e829316cbcd6f35c88eeabccfe6/semmed/relations.csv', 'hf://datasets/DevWithKaiju/cell-cell-communication@206ebee01c426e829316cbcd6f35c88eeabccfe6/semmed/seed_splits.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id int64 | pmid int64 | label int64 | entity_a_id string | entity_b_id string | sentence_start int64 | sentence_end int64 | entity_a_start string | entity_a_end string | entity_b_start string | entity_b_end string |
|---|---|---|---|---|---|---|---|---|---|---|
0 | 10,727,789 | 0 | CL:0005024 | CL:0011102 | 338 | 650 | 429 | 447 | 497 | 519 |
3 | 7,527,588 | 0 | CL:1000326 | CL:0000849 | 417 | 581 | 471 | 488 | 493 | 503 |
6 | 29,308,690 | 0 | CL:1000497 | CL:0000540 | 937 | 1,128 | 1088 | 1099 | 1120 | 1126 |
8 | 18,223,171 | 0 | CL:0000553 | CL:0000556 | 139 | 448 | 236 | 266 | 156 | 169 |
9 | 37,476,833 | 0 | CL:0000850 | CL:1001474 | 970 | 1,235 | 1103 | 1122 | 1041 | 1060 |
13 | 21,277,755 | 0 | CL:4033017 | CL:0002598 | 651 | 856 | 762 | 792 | 731 | 759 |
15 | 16,626,650 | 0 | CL:0011113 | CL:0000540 | 345 | 681 | 528 | 550 | 650 | 656 |
18 | 32,450,529 | 0 | CL:1000143 | CL:0000097 | 991 | 1,151 | 1028 | 1044 | 1140 | 1149 |
19 | 16,160,858 | 0 | CL:0000635 | CL:1000191 | 1,040 | 1,430 | 1312 | 1324 | 1298 | 1309 |
21 | 26,066,485 | 0 | CL:0000820 | CL:0000094 | 0 | 217 | 83 | 94 | 109 | 120 |
22 | 15,289,640 | 0 | CL:0008024 | CL:0002079 | 286 | 425 | 339 | 364 | 311 | 333 |
25 | 7,161,476 | 0 | CL:0000103 | CL:0000540 | 683 | 929 | 870 | 884 | 830|921 | 836|927 |
26 | 37,450,589 | 0 | CL:0002548 | CL:0000746 | 411 | 676 | 554 | 572 | 535 | 548 |
27 | 2,590,527 | 0 | CL:0002616 | CL:0000136 | 379 | 729 | 394 | 413 | 697 | 706 |
28 | 6,661,754 | 1 | CL:0002151 | CL:0002154 | 217 | 435 | 279 | 296 | 259 | 277 |
29 | 8,977,424 | 0 | CL:0002561 | CL:0000010 | 173 | 359 | 322 | 344 | 183 | 196 |
30 | 3,970,854 | 0 | CL:0002192 | CL:0000775 | 136 | 405 | 181 | 194 | 155|311 | 165|321 |
31 | 3,881,622 | 0 | CL:0000500 | CL:0000236 | 884 | 1,311 | 1237 | 1263 | 1057 | 1069 |
32 | 36,561,369 | 0 | CL:2000060 | CL:3000001 | 597 | 950 | 672 | 695 | 843 | 856 |
34 | 20,336,528 | 0 | CL:0000169 | CL:0000540 | 636 | 866 | 844 | 864 | 816 | 822 |
36 | 31,164,635 | 1 | CL:0002241 | CL:0000235 | 1,396 | 1,583 | 1519 | 1552 | 1444 | 1454 |
38 | 10,891,875 | 0 | CL:4023119 | CL:0000561 | 439 | 583 | 486 | 509 | 456 | 469 |
40 | 7,691,107 | 0 | CL:0008028 | CL:0000540 | 656 | 823 | 801 | 821 | 770 | 776 |
41 | 10,228,131 | 0 | CL:0000158 | CL:0002368 | 1,090 | 1,245 | 1168 | 1178 | 1139 | 1161 |
43 | 3,712,006 | 0 | CL:0000166 | CL:0000540 | 587 | 765 | 697 | 712 | 721 | 727 |
44 | 3,047,146 | 0 | CL:0000692 | CL:0000218 | 1,549 | 1,992 | 1926 | 1947 | 1805 | 1829 |
45 | 30,139,179 | 0 | CL:0000718 | CL:0000147 | 156 | 405 | 215 | 226 | 260|289 | 272|301 |
46 | 18,753,258 | 0 | CL:0002188 | CL:0000653 | 228 | 484 | 369 | 396 | 355 | 363 |
47 | 30,868,438 | 0 | CL:0002079 | CL:0011026 | 935 | 1,201 | 987 | 1009 | 1140 | 1155 |
48 | 26,651,604 | 0 | CL:3000004 | CL:0000540 | 354 | 579 | 552 | 577 | 439 | 445 |
50 | 19,741,101 | 0 | CL:0000678 | CL:0000598 | 491 | 891 | 690 | 708 | 750 | 767 |
52 | 15,017,036 | 0 | CL:0000881 | CL:0000576 | 431 | 706 | 582 | 605 | 665 | 673 |
58 | 20,425,127 | 0 | CL:0002148 | CL:0000060 | 545 | 706 | 688 | 704 | 599 | 610 |
59 | 9,068,861 | 0 | CL:0004218 | CL:0004217 | 1,285 | 1,446 | 1411 | 1429 | 1319|1363 | 1337|1381 |
60 | 33,605,542 | 0 | CL:0000783 | CL:0000092 | 0 | 177 | 38 | 62 | 15 | 25 |
61 | 9,089,069 | 0 | CL:4030037 | CL:0000586 | 0 | 339 | 176 | 195 | 214 | 223 |
62 | 2,123,224 | 0 | CL:0002652 | CL:0000094 | 1,030 | 1,246 | 1064 | 1072 | 1099 | 1110 |
65 | 19,438,538 | 0 | CL:0002060 | CL:2000000 | 0 | 217 | 204 | 215 | 150 | 170 |
67 | 26,046,449 | 1 | CL:0002150 | CL:0000775 | 315 | 585 | 412 | 434 | 473 | 483 |
71 | 18,642,027 | 0 | CL:0007001 | CL:0000062 | 551 | 688 | 605 | 622 | 642 | 652 |
72 | 12,172,789 | 0 | CL:4023119 | CL:0000561 | 987 | 1,229 | 1089 | 1112 | 1032 | 1045 |
73 | 2,005,236 | 0 | CL:4023092 | CL:0000122 | 627 | 787 | 749 | 774 | 717 | 732 |
75 | 1,591,357 | 1 | CL:4030022 | CL:0000233 | 964 | 1,274 | 1179 | 1205 | 1089 | 1097 |
76 | 33,402,445 | 0 | CL:0000855 | CL:0000540 | 1,241 | 1,474 | 1417 | 1434 | 1390 | 1396 |
77 | 28,744,287 | 0 | CL:0000973 | CL:0000084 | 371 | 634 | 508 | 525 | 602 | 608 |
78 | 30,227,405 | 0 | CL:0001201 | CL:0000786 | 720 | 1,005 | 843 | 855 | 985 | 996 |
79 | 34,654,783 | 0 | CL:1000692 | CL:1000742 | 522 | 798 | 574 | 604 | 528 | 553 |
81 | 2,022,361 | 0 | CL:0000517 | CL:0000235 | 1,297 | 1,495 | 1443 | 1471 | 1430 | 1440 |
82 | 7,665,926 | 0 | CL:1001606 | CL:0000312 | 0 | 202 | 133 | 154 | 170 | 182 |
83 | 2,482,572 | 0 | CL:0000185 | CL:0000646 | 475 | 920 | 754 | 772 | 703 | 713 |
84 | 26,608,187 | 0 | CL:0000581 | CL:0000235 | 1,348 | 1,546 | 1357 | 1378 | 1534 | 1544 |
85 | 25,605,129 | 0 | CL:0005018 | CL:0000164 | 464 | 714 | 598 | 620 | 504 | 524 |
87 | 1,086,865 | 0 | CL:0000983 | CL:0000084 | 2,017 | 2,235 | 2203 | 2218 | 2055 | 2061 |
88 | 2,685,109 | 0 | CL:0005015 | CL:0002084 | 365 | 547 | 397 | 418 | 421 | 437 |
90 | 30,177,258 | 0 | CL:0000973 | CL:0000084 | 408 | 605 | 522 | 539 | 556 | 562 |
92 | 36,089,294 | 0 | CL:0000185 | CL:0000066 | 122 | 301 | 220 | 238 | 202 | 217 |
94 | 20,437,528 | 0 | CL:0005024 | CL:0000108 | 381 | 554 | 532 | 552 | 407 | 425 |
96 | 37,899,991 | 0 | CL:0000034 | CL:0000037 | 0 | 221 | 188 | 197 | 53 | 76 |
99 | 6,972,740 | 0 | CL:0000525 | CL:0011101 | 598 | 796 | 666|718 | 690|742 | 768 | 794 |
100 | 9,916,685 | 0 | CL:4030001 | CL:0000816 | 0 | 259 | 24 | 43 | 126 | 141 |
101 | 34,011,609 | 0 | CL:0000675 | CL:0000300 | 223 | 563 | 277 | 290 | 467 | 473 |
106 | 10,526,261 | 0 | CL:0002615 | CL:0000136 | 1,094 | 1,359 | 1228 | 1244 | 1188 | 1196 |
107 | 29,466,392 | 0 | CL:0000322 | CL:0000235 | 257 | 592 | 524 | 548 | 493 | 503 |
108 | 17,084,823 | 0 | CL:4023181 | CL:0000125 | 521 | 716 | 652 | 667 | 558 | 568 |
110 | 37,202,489 | 0 | CL:0009104 | CL:0000236 | 0 | 189 | 0 | 26 | 109 | 115 |
117 | 37,759,733 | 0 | CL:0002097 | CL:0000128 | 208 | 336 | 264 | 283 | 246 | 261 |
118 | 35,177,137 | 0 | CL:0000848 | CL:0000847 | 0 | 177 | 113 | 150 | 69 | 102 |
119 | 22,539,980 | 0 | CL:4023161 | CL:0011005 | 796 | 1,068 | 954 | 973 | 994 | 1015 |
120 | 35,245,615 | 1 | CL:0000863 | CL:0000235 | 917 | 1,074 | 1039 | 1062 | 942 | 952 |
124 | 6,380,843 | 0 | CL:0017006 | CL:0017005 | 275 | 851 | 773 | 786 | 649 | 660 |
125 | 36,644,256 | 0 | CL:0000594 | CL:0011026 | 0 | 302 | 190 | 220 | 74|165 | 89|180 |
126 | 39,089,472 | 0 | CL:0000112 | CL:0000540 | 639 | 976 | 691 | 706 | 680|900 | 686|906 |
128 | 6,322,745 | 1 | CL:0000547 | CL:0000558 | 239 | 509 | 375 | 390 | 495 | 507 |
129 | 19,175,993 | 0 | CL:0000580 | CL:0000549 | 402 | 1,085 | 664 | 686 | 776 | 794 |
130 | 27,223,328 | 0 | CL:0000678 | CL:0005000 | 165 | 358 | 338 | 356 | 298 | 321 |
131 | 36,376,057 | 0 | CL:0002481 | CL:0000216 | 842 | 1,011 | 888 | 910 | 842 | 854 |
132 | 21,557,937 | 0 | CL:0000510 | CL:0000160 | 216 | 422 | 382 | 393 | 350 | 361 |
135 | 1,371,903 | 0 | CL:0000849 | CL:0000570 | 309 | 635 | 487 | 497 | 597 | 616 |
136 | 15,155,310 | 0 | CL:4028001 | CL:0000738 | 1,533 | 1,688 | 1650 | 1686 | 1563|1603 | 1572|1612 |
139 | 9,858,230 | 0 | CL:0000556 | CL:0000233 | 1,343 | 1,625 | 1549 | 1562 | 1392|1523 | 1400|1531 |
140 | 17,548,583 | 0 | CL:0000960 | CL:0000236 | 183 | 383 | 265 | 274 | 304 | 310 |
141 | 3,500,260 | 1 | CL:0000973 | CL:0000084 | 0 | 199 | 0 | 17 | 157 | 163 |
142 | 33,728,096 | 0 | CL:0002167 | CL:0002368 | 692 | 978 | 839 | 864 | 773 | 795 |
146 | 33,177,165 | 0 | CL:1000347 | CL:0000097 | 1,212 | 1,499 | 1242 | 1252 | 1387 | 1396 |
147 | 12,355,421 | 0 | CL:4023119 | CL:0000740 | 618 | 808 | 783 | 806 | 755 | 776 |
148 | 8,768,837 | 0 | CL:0002620 | CL:0000738 | 908 | 1,036 | 1019 | 1034 | 982 | 991 |
149 | 38,229,856 | 0 | CL:0002562 | CL:0000346 | 105 | 257 | 222 | 247 | 183 | 216 |
151 | 3,026,881 | 0 | CL:0002567 | CL:0000574 | 133 | 399 | 264 | 286 | 140 | 152 |
152 | 11,536,282 | 0 | CL:2000029 | CL:0002139 | 1,528 | 1,713 | 1682 | 1711 | 1648 | 1673 |
154 | 22,526,887 | 0 | CL:1000001 | CL:0000540 | 508 | 737 | 670 | 699 | 655 | 661 |
155 | 33,670,139 | 0 | CL:0000682 | CL:0000542 | 894 | 1,283 | 1104 | 1110 | 1203 | 1213 |
156 | 38,254,943 | 0 | CL:0011025 | CL:0000910 | 1,424 | 1,752 | 1620 | 1636 | 1579 | 1595 |
158 | 2,458,167 | 0 | CL:0011110 | CL:0000540 | 0 | 340 | 199 | 219 | 296 | 302 |
159 | 38,493,915 | 0 | CL:0000448 | CL:0001070 | 1,487 | 1,629 | 1500 | 1515 | 1584 | 1599 |
163 | 11,971,865 | 0 | CL:0000868 | CL:0000871 | 1,006 | 1,153 | 1113 | 1134 | 1057 | 1075 |
164 | 24,681,493 | 0 | CL:0010001 | CL:0002139 | 484 | 651 | 554 | 578 | 584 | 609 |
165 | 20,089,859 | 0 | CL:0002583 | CL:0000136 | 663 | 810 | 719 | 744 | 784 | 793 |
166 | 16,855,267 | 0 | CL:1001516 | CL:0000212 | 573 | 726 | 594 | 625 | 709 | 724 |
168 | 16,118,350 | 0 | CL:0002402 | CL:0000182 | 1,237 | 1,395 | 1306 | 1326 | 1332 | 1342 |
171 | 12,930,778 | 0 | CL:0000735 | CL:0011008 | 127 | 304 | 282 | 302 | 258 | 276 |
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